Transcript Slide 1

Decision Support Systems
Chapter 3
Decision Support Systems:
An Overview
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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Outline
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1.Decision Support Systems.
2.Characteristics and capabilities of DSS.
3. DSS components.
4. Data Management Subsystem.
5. Model Management Subsystem.
6. User Interface system
7. Knowledge-based Management System
8. DSS Hardware.
9. DSS classification.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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1.Decision Support Systems
• Systems designed to support managerial
decision-making in unstructured problems
• More recently, emphasis has shifted to
inputs from outputs
• Mechanism for interaction between user
and components
• Usually built to support solution or evaluate
opportunities
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DSS
• A DSS is a methodology that supports
decision-making.
• It is:
– Flexible;
– Adaptive;
– Interactive;
– GUI-based;
– Iterative; and
– Employs modeling.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
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2. Characteristics and capabilities
of DSS
• Because there is no consensus on exactly what a
DSS is, there is no agreement on standard
characteristics and capabilities of DSS.
• The term “business intelligence” is synonymous
with DSS
• The list in the following figure is an ideal set.
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© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
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Business Intelligence
• Proactive BI focusses on accelerating
decision-making
• Increases information flows
• Five components of proactive BI:
– Real-time warehousing
– Exception and anomaly detection
– Proactive alerting with automatic recipient
determination
– Seamless follow-through workflow
– Automatic learning and refinement
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3. Components of DSS
• Subsystems:
– Data management
• Managed by DBMS
– Model management
• Managed by MBMS
– User interface
– Knowledge Management and
organizational knowledge base
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4.Data Management Subsystem
• Components:
– Database
– Database management system
– Data directory
– Query facility
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Turban, Aronson, and Liang
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Database
• A database is a collection of interrelated
data extracted from various sources, stored
for use by the organization, and queried.
• The data from the DSS database are
extracted from:
– Internal data, usually from TPS
– External data from government agencies, trade
associations, market research firms, forecasting
firms
– Private data or guidelines used by decisionmakers
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Database Management System
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Extracts data
Manages data and their relationships
Updates (add, delete, edit, change)
Retrieves data (accesses it)
Queries and manipulates data
Employs data dictionary
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Data Directory
• Catalog of all data
– Contains data definitions
– Answers questions about the availability
of data items
– Source
– Meaning
– Allows for additions, removals, and
alterations
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5.Model Management Subsystem
• Model management subsystem of a
DSS consists of the components:
– Model base
– Model base management system
– Modeling language
– Model directory
– Model execution, integration, and
command processor
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The structure of the model management subsystem
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Category of Models
• Strategic
– Supports top management decisions
• Tactical
– Used primarily by middle management
to allocate resources
• Operational
– Supports daily activities
• Analytical
– Used to perform analysis of data
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Model Base Management System
• Functions:
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Model creation
Model updates
Model data manipulation
Generation of new routines
• Model directory:
– Catalog of models
– Definitions
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Model Management Activities
• Model execution
– Controls running of model
• Model command processor
– Receives model instructions from user interface
– Routes instructions to MBMS or module
execution or integration functions
• Model integration
– Combines the operations of several models
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6.User Interface System
Data management
and DBMS
Knowledge-based
system
Model
management and
MBMS
User Interface Management System (UIMS)
Natural Language Processor
Input
Action
Languages
Based on Figure 3.6, Schematic
View of the User Interface
Users
Output
Display
Language
PC Display
Printers, Plotters
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User Interface Management
System
• GUI
• Natural language processor
• Interacts with model management
and data management subsystems
• Examples
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Speech recognition
Display panel
Tactile interfaces
Gesture interface
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7.Knowledge-Base Management
System
• Many unstructured/semistructured problems need
expertise (knowledge) for their solutions.
• Such expertise can be provided by some knowledge
engineers who interview the domain experts and
gather the information necessary for the knowledgebase.
• More advanced DSSs are equipped with a component
called knowledge base management subsystem.
• This subsystem can achieve complex problem solving
and it can enhance operations of other components.
• The knowledge base is where the “knowledge” of the
DSS is stored. By knowledge, we mean the rules,
heuristics, constraints, previous outcomes and any
other “knowledge” that may have been programmed
into the DSS.
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Knowledge retrieval
• Once we have the knowledge stored in the
knowledge base, we need a method of getting
them out in an organized fashion. The inference
engine (IE) is that part of the knowledge base that
facilitates this process.
• The IE is the module that activates all the domain
knowledge that has been gathered and performs
inferencing (reasoning) to work toward a solution
or conclusion.
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8. DSS Hardware
• De facto standard
• Web server with DBMS:
– Operates using browser
– Data stored in variety of databases
– Can be mainframe, server, workstation,
or PC
– Any network type
– Access for mobile devices
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9.DSS Classifications
• Alter
– Extent to which outputs can directly support or
determine the decision
– Data-oriented or model-oriented
• Holsapple and Whinston
– Text-oriented, database-oriented, spreadsheetoriented, solver-oriented, rule-oriented, or
compound
• Intelligent DSS
– Knowledge-based DSS, rule-oriented DSS
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Notes on Solver-oriented DSS
• A solver is an algorithm or procedure written as a
program for performing certain computation for
solving a particular problem type.
• EX: linear regression routine, linear programming
routine.
• Solver can be written in a programming languages
such as C++, Java.
• DSS builder can incorporate the solver in creating
the DSS application.
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(ad hoc analysis)
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Other DSS Classifications
• Donovan and Madnick
– Institutional (Problems of recurring
nature)
– Ad hoc (Problems that are not
anticipated or are not repetitive)
• Hackathorn and Keen
– Personal support,
– Group support, or organizational support
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DSS Classifications
• Group SS v. Individual DSS
– Decisions made by entire group or by
lone decision maker
• Custom-made v. vendor-ready-made
– Generic DSS may be modified for use
• Database, models, interface, support are
built in
• Addresses repeatable industry problems
• Reduces costs
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Web and DSS
• The web can be used for data collection
• The Web can be used for communications and
collaborations
• The Web can be used to download DSS software.
• Database vendors provide Web capabilities by
running directly on Web servers
• Simplifies integration problems
• Increased usability features
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Turban, Aronson, and Liang
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